Network Modeling of Liver Metabolism to Predict Plasma Metabolite Changes During Short-Term Fasting in the Laboratory Rat

Animal Kernicterus Models: Progress and Challenges

Kernicterus is a leading cause of neonatal death throughout the world, especially in low-middle-income countries. It is developed by an unconjugated hyperbilirubinemia in the blood and brain tissue, triggering pathological processes that spawn neurotoxicity and neurodegeneration. However, the biological mechanism (s) of bilirubin-induced neurotoxicity and Kernicterus development remain to be well elucidated. Likewise, a practical therapeutic approach for human Kernicterus has yet to be found. Undoubtedly, animal models of Kernicterus can be helpful in the identification of underlying biological processes of hyperbilirubinemia evolution to Kernicterus, as well as the evaluation of various treatments efficacy in preclinical studies. More importantly, establishing an animal model that can mimic the Kernicterus and its behavioral, neuro-histological, and hematological manifestations is a severe priority in preclinical studies. So far, several Kernicterus animal models have been established that could partially mimic one or more clinical and paraclinical signs of human Kernicterus. The present study aimed to review all methods modeling Kernicterus with a focus on their potentials and shortcomings and subsequently provide the optimal methods for an ideal Kernicterus animal model.

Insulin Resistance in Apolipoprotein M Knockout Mice is Mediated by the Protein Kinase Akt Signaling Pathway

BACKGROUND

Previous clinical studies have suggested that apolipoprotein M (apoM) is involved in glucose metabolism and plays a causative role in insulin sensitivity.

OBJECTIVE

The potential mechanism of apoM on modulating glucose homeostasis is explored and differentially expressed genes are analyzed by employing ApoM deficient (ApoM-/- ) and wild type (WT) mice.

METHODS

The metabolism of glucose in the hepatic tissues of high-fat diet ApoM-/- and WT mice was measured by a glycomics approach. Bioinformatic analysis was applied for analyzing the levels of differentially expressed mRNAs in the liver tissues of these mice. The insulin sensitivity of ApoM-/- and WT mice was compared using the insulin tolerance test and the phosphorylation levels of protein kinase Akt (AKT) and insulin stimulation in different tissues were examined by Western blot.

RESULTS

The majority of the hepatic glucose metabolites exhibited lower concentration levels in the ApoM-/- mice compared with those of the WT mice. Gene Ontology (GO) classification and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that ApoM deficiency affected the genes associated with the metabolism of glucose. The insulin tolerance test suggested that insulin sensitivity was impaired in ApoM-/- mice. The phosphorylation levels of AKT in muscle and adipose tissues of ApoM-/- mice were significantly diminished in response to insulin stimulation compared with those noted in WT mice.

CONCLUSION

ApoM deficiency led to the disorders of glucose metabolism and altered genes related to glucose metabolism in mice liver. In vivo data indicated that apoM might augment insulin sensitivity by AKT-dependent mechanism.

Genome-scale metabolic model of the rat liver predicts effects of diet restriction

Mapping network analysis in cells and tissues can provide insights into metabolic adaptations to changes in external environment, pathological conditions, and nutrient deprivation. Here, we reconstructed a genome-scale metabolic network of the rat liver that will allow for exploration of systems-level physiology. The resulting in silico model (iRatLiver) contains 1,882 reactions, 1,448 metabolites, and 994 metabolic genes. We then used this model to characterize the response of the liver’s energy metabolism to a controlled perturbation in diet. Transcriptomics data were collected from the livers of Sprague Dawley rats at 4 or 14 days of being subjected to 15%, 30%, or 60% diet restriction. These data were integrated with the iRatLiver model to generate condition-specific metabolic models, allowing us to explore network differences under each condition. We observed different pathway usage between early and late time points. Network analysis identified several highly connected “hub” genes (Pklr, Hadha, Tkt, Pgm1, Tpi1, and Eno3) that showed differing trends between early and late time points. Taken together, our results suggest that the liver’s response varied with short- and long-term diet restriction. More broadly, we anticipate that the iRatLiver model can be exploited further to study metabolic changes in the liver under other conditions such as drug treatment, infection, and disease.